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All Journal e-Dinamis ELT Worldwide: Journal of English Language Teaching KAREBA : Jurnal Ilmu Komunikasi Jurnal Penelitian Sains JURNAL MEDIA INFORMATIKA BUDIDARMA BERDIKARI : Jurnal Inovasi dan Penerapan Ipteks UICELL Conference Proceeding Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat IJISH (International Journal of Islamic Studies and Humanities) LISANAN ARABIYA: Jurnal Pendidikan Bahasa Arab Mobile and Forensics Signal and Image Processing Letters Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal English Teaching and Linguistics Journal (ETLiJ) Al-Fathin: Jurnal Bahasa dan Sastra Arab Letters in Information Technology Education (LITE) Jurnal Kesehatan Tambusai Jurnal Jarlit JTechLP El 'Aailah Journal Medical Informatics Technology Bulletin of Social Informatics Theory and Application International Journal of Business English and Communication (IJoBEC) Jurnal Literasi dan Pembelajaran Indonesia Celebes Journal of Language Studies QOSIM: Jurnal Pendidikan, Sosial & Humaniora Journal of Sustainable Community Development GEMBIRA (Pengabdian Kepada Masyarakat) Multidisciplinary Indonesian Center Journal Journal on Mathematics Education Signal and Image Processing Letters Axiology
Ahmad Azhari
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Journal : Signal and Image Processing Letters

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Multinomial Naïve Bayes for Sentiment Analysis of Indonesian's Local Government Performance Azhari, Ahmad; Hadi, Muhammad Saepul
Signal and Image Processing Letters Vol 3, No 2 (2021)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v3i2.22

Abstract

Digitalization of government performance, in conveying information and getting criticism, suggestions, and complaints from the public, is currently being carried out using social media. The use of social media is a form of government responsibility and openness to society. The high number of Twitter users in Indonesia, which reaches 6.43 million, allows the government to get many responses from the public. This background provides an opportunity for the public to be able to measure government performance based on a number of criticisms, suggestions, and complaints that the government responds to. However, public sentiment towards government performance has not been used as an evaluation and benchmark for the government in determining policies. The purpose of this research is to build a social media twitter sentiment analysis system to measure public sentiment towards local government performance by implementing Multinomial Naïve Bayes. This research is divided into several stages including tweet grabbing, manual tweet filtering, tweet labeling, split tweets, preprocessing tweets, term frequency, classification, and evaluation. The tweet retrieval process was carried out on 1 June - 31 July 2020 with 2000 tweets used from the total tweets obtained after manual filtering was carried out. This study shows that the sentiment analysis carried out obtained an accuracy of 80%, a precision of 78%, and a recall of 82%.
Classification of Interests and Talents in Early Adult Phase Based on RMIB Test with Neural Network Azhari, Ahmad; Jaya, Erlangga
Signal and Image Processing Letters Vol 4, No 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v4i2.24

Abstract

The brain in the human body is responsible for regulating the overall work of the human body and mind. The left part of the brain is the center of intelligence or commonly called Intelligence Quotient (IQ).  Intelligence can come from genes received by children from their parents that will continue to develop along with a person's maturity process.  An individual will go through a transition period or transition period, namely in the early adult phase so that individuals in the early adult phase often experience unstable psychic conditions. This labile condition occurs in early adult individuals in this case, namely students who are still not sure what potential interests and talents they have, causing students It felt wrong to take the major. The purpose of this study is to classify interests and aptitudes from EEG data obtained from interviewees with RMIB test stimulus. In this study, testing will be carried out on the object of study where the   object of study is an individual in the early adult phase with an age range between 18-30 years. The test is carried out using a beta signal (12-30 Hz) resulting from an Electroencephalogram (EEG) signal filter generated from recording EEG data with the NeuroSky Mindwave tool and then reduced to get the best value or component with the Principal Component Analysis (PCA) method.  EEG data recording is carried out 3 times with data recording intervals every 14 days. EEG data is   information that we can get from activity waves in the brain, because waves in the brain cannot be observed visually. Testing on this study.  The EEG data obtained will go through the pre-processing stage, namely signal filters and signal reduction   and then will be classified using neural networks with a backpropagation algorithm with Using 1 layer of hidden layer. In this study, the results of the RMIB test carried out by the interviewees were calculated by psychologists (expert judgement) which were used as comparison data or the output produced by the system.   Testing is carried out by cross validation, which is to cross-test each data retrieval. Accuracy testing on the first fetch resulted in an accuracy of 92.8571%, in the second data retrieval it produced an accuracy of 78.571%, in the third data retrieval it resulted in an accuracy of 71.4285% with an average accuracy produced by the system of 80.9523%.
Pitumpanua Community Complaint Service Based on Software Development Life Cycle Arief, Husniah; Azhari, Ahmad
Signal and Image Processing Letters Vol 5, No 3 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v5i3.97

Abstract

Public services generally only provide suggestion box to people who have complaints. In the ongoing complaints, namely the people use written media (suggestion and complaint boxes) and oral media (face to face with employees). The complaint handling system is not stored in the database which causes the unknown number of complaints that have or have not handled so that the handling of complaints is delayed or skipped. Every complaint that is recorded manually will attack the search for data and is not efficient because complaints must be met directly and do not rule out data being damaged or lost because there is no backup. This study aims to develop a Community Complaint Application in the Pitumpanua District and to find out the results of testing the Community Complaint Application in the Pitumpanua District. This study uses a model waterfall development with data collection techniques using techniques interviews, and questionnaires to measure the feasibility of the device software that has been developed with several Respondentts. System testing in this study uses several standards the quality of software development, namely ISO 25010, among others are functional suitability with good category results, very good usability, portability with good category results, Based on the results research is produced a Complaint Application Development Website-Based Society that can be used to make public complaints and manage the administration of public complaint reports.
Identification of Infant Crying Using Mel-Frequency Cepstral Coefficient (MFCC) and Artificial Neural Network (ANN) Methods Azhari, Ahmad; Destiyanti, Intan
Signal and Image Processing Letters Vol 4, No 3 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v4i3.70

Abstract

The crying of infants aged 0-3 months can be classified according to their needs, as identified by Dunstan Baby Language, which consists of specific sounds denoting different needs. These sounds include "eairh" for discomfort caused by fart, "neh" indicating hunger, "heh" representing general discomfort, "owh" signaling tiredness or sleepiness, and "eh" expressing the need to burp. The baby crying sound data was obtained from the Dunstan Baby Language (DBL) database, which includes educational videos about infants and a collection of babies crying sounds. These sounds were converted into *.wav audio format and divided into 5-second segments. A total of 188 audio data segments were collected. The research employed the Artificial Neural Network (ANN) classification method and the Mel-Frequency Cepstral Coefficient (MFCC) feature extraction method. The collected data underwent feature extraction, aiming to identify distinctive characteristics using the librosa library in the Python programming language. This process allowed us to obtain specific information from the acquired sound data. The results of this study achieved an accuracy level of 90%. This research contributes to the understanding and classification of infant crying based on the Dunstan Baby Language, offering insights into their various needs. The implementation of ANN and MFCC techniques showcases the effectiveness of this approach in accurately classifying infant cries and provides a foundation for further research in the field of infant communication.
Analysis the Effects of Games on Cognitive Activity of Late Adolescents Using the Electroencephalogram with the K-Nearest Neighbor Method Azhari, Ahmad; Swara, Ajie Kurnia Saputra
Signal and Image Processing Letters Vol 2, No 1 (2020)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v2i1.20

Abstract

The influence of violent video games on child development continues to be a polemic, Various pros and cons also color this problem, because in adolescence not only adopt cognitive abilities in learning activities, but also various strategies related to managing activeness in learning, playing and socializing to improve cognitive abilities.  Adolescents who are addicted to online games are included in the three criteria set by WHO (Word Health Organization), namely that they need games with symptoms of withdrawing from the environment, losing control, and not caring about other activities (Santoso and Purnomo, 2017).  The purpose of this study is to analyze the cognitive activity of late adolescence between learning and playing games and knowing that games can have a good or bad impact on the cognitive activity of adolescents. The application of the K-Nearest Neighbor method to the system created can classify with prediction results on the influence of games on the cognitive activity of adolescents using Electroencephalogram (EEG) data and can also provide information in the form of new predictions on the respondent data obtained. The results of the analysis resulted in a percentage of accuracy in the game stimulus data of 80%, and in the cognitive stimulus data, namely SPM, it got an accuracy of 80% using the same K value in both stimuli, namely 1, 6, and 7. While the expert results on the system the percentage of superior but addicted respondents was 63.3% and the percentage of respondents who were average but addicted was 36.6% with a correlation rate between Games and SPM of 0.089822409. Based on the results of this study, it can be concluded that the percentage obtained from the comparison of the results of the expert to the results of the system and the comparison of the system itself does not have the influence of games on cognitive activity in late adolescence.
UAD Lecturer's Introductory System Through Surveillance Cameras with Eigenface Method Azhari, Ahmad; Sahadi, Syah Reza Pahlevi
Signal and Image Processing Letters Vol 4, No 1 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v4i1.23

Abstract

Technologies related to processing using computers are developing so rapidly, such as applications to identify a person automatically through camera monitors (CCTV). The human recognition application in real time can be found in the surveillance system, identification and facial recognition. The direct observation of human beings has a weakness such as fatigue and saturation that may occur, resulting in decreased accuracy. For that, computer can be an alternative solution to overcome it. For example, the human Face Recognition (Eigenface) detection system. This system can be very helpful when you want to find and know the existence of someone in a place, for example to help in finding the existence of lecturers on campus. Students often seek lecturers to conduct guidance or for other academic matters, but students often do not know whether the lecturers sought on campus or not. Therefore, in this research an application will be made to help students in knowing the existence of lecturers on campus. This final project examines the system to recognize lecturers who are on campus using CCTV. The method used is eigenface. Eigenface is one of the facial pattern recognition algorithms based on the Principle Component Analysis (PCA). The basic principle of facial recognition is to cite the unique information of the face and then be encoded and compared with the previously done decode result. The process itself consists of data collection and facial recognition processes. In the process of collecting data, the data taken in the form of the name and the image of the lecturer will be used as a database to recognize the face of the lecturer. While the facial recognition process is the process by which the face of the lecturer who has been caught by the camera will be compared with the database that has been taken to recognize the lecturer. From the research done can be concluded that there are several factors that affect the accuracy of the system including the distance of the camera sensor with the most effective object is 1 to 2 meters, the intensity of bright or dim light, the face positioning and Number of datasets owned. The test results obtained an accuracy of 89%.
Implementation Method Forward Chaining in Game Puzzle (Case Study in Paud Dini Laras Yogyakarta) Azhari, Ahmad; Dharma Ariawan, Ade
Signal and Image Processing Letters Vol 3, No 1 (2021)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v3i1.32

Abstract

In the early childhood education stage, children will tend to be more interested in easy-to-play games that have animated images that attract attention. Whereas currently in learning PAUD children still use the game method using paper media so that the games provided will make children feel bored. This study aims to conduct a new teaching media approach namely Puzzle educational games using the Forward Chaining method as a research topic on compiling desktop-based images and games for PAUD children at DUD Laras Yogyakarta. This research uses Forward Chaining method as an implementation in a Puzzle Game that is R1 is the first rule that is known fact is the Random Puzzle box contained in each scene, R2 is the 2nd rule of the reasoning process when the matching premise is wrong then there is a temporary premise namely the trash box that hold until all the premises are properly matched, R3 is the 3rd rule that is the time and score as a conclusion the game can continue until the game is finished. This research resulted in 2 times Game testing. The first test using black box testing game application is correct and has no malfunction on the button and is feasible to be implemented. And the second test is the quality testing that has been done by testing the choice of answer categories from the questionnaire that has been distributed in the field, it can be concluded that the Puzzle Game is made easy to use and has a pretty good appearance and content suitable for early childhood play (PAUD).
K-Nearest Neighbor Classification for Detection of The Effect of Game Addiction on Cognitive Activity in The Late Adolescent Phase based on Brainwave Signals Azhari, Ahmad; Swara, Ajie Kurnia Saputra
Signal and Image Processing Letters Vol 1, No 2 (2019)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v1i2.5

Abstract

World Health Organization (WHO) has determined that Gaming disorder is included in the International Classification of Diseases (ICD-11). The behavior of playing digital games included in the Gaming disorder category is characterized by impaired control of the game, increasing the priority given to the game more than other activities insofar as the game takes precedence over other daily interests and activities, and the continuation or improvement of the game despite negative consequences. The influence of video games on children's development has always been a polemic because in adolescence not only adopts cognitive abilities in learning activities, but also various strategies related to managing activities in learning, playing and socializing to improve cognitive abilities. Therefore, this research was conducted to analyze the cognitive activity of late teens in learning and playing games based on brainwave signals and to find out the impact of games on cognitive activity in adolescents. Prediction of the effect of the game on cognitive activity will be done by applying Fast Fourier Transform for feature extraction and K-Nearest Neighbor for classification. The results of the expert assessment showed the percentage of respondents with superior cognitive category but game addiction was 63.3% and respondents with cognitive categorization were average but were addicted by 36.6%. The percentage of accuracy produced by the system shows 80% in games and cognitive by using k values of 1, 6, and 7. The correlation test results show a percentage of 0.089, so it is concluded that there is no influence of the game on cognitive activity in late adolescents.
Product Selection of Face Masks for Sensitive Skin Using the Composite Performance Index (CPI) Method Nugroho, Prasetiyanto; Azhari, Ahmad
Signal and Image Processing Letters Vol 5, No 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v5i2.95

Abstract

The more face mask products for sensitive facial skin that are created, consumers also feel confused by several considerations such as excessive side effects for the mask products they will use so as not to worsen the condition of the facial skin. Therefore, to help consumers in choosing the right face mask in terms of consideration of benefits, side effects that will be caused, and affordable prices, the authors compiled a study with the title "Selection of Face Mask Products for Sensitive Skin Using the Composite Performance Index (CPI) Method". Composite Performance Index (CPI) was chosen because this method is good at decision making and the calculation process of the CPI method only requires the criteria value of several alternatives which when compared to the CPI method process is shorter. This method can be used to determine the assessment or ranking of various alternatives based on several criteria. Criteria values are inputs that have been entered and converted into numbers. While the alternative value is the weighting obtained from the calculation of multiplication, addition of ingredients or division of each criterion. The result of this research is that the assessment process can be carried out from each mask product using the criteria of price, skin condition, mask benefits and consumer age. The system can determine the best mask for sensitive skin by implementing the Composite Performance Index (CPI) method with the results of the website validity test getting a percentage of 85.34% with a very good interpretation.
Classification of concentration or focus by signal Electroencephalography (EEG) and addiction Watching K-Dramas Using Algoritma K-Nearest Neighbor Azhari, Ahmad; Ramadan, Rizky
Signal and Image Processing Letters Vol 1, No 3 (2019)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v1i3.26

Abstract

K-drama or drakor is currently being enjoyed in Indonesia when the Covid-19 pandemic hits, especially by the fair sex. From the sources obtained, the number of k-dramas or dramas also increased during the covid-19 pandemic from the previous 2.7 hours a day to 4.6 hours a day. The issue raised by the authors in this study is whether the impressions of drakor will later affect the concentration of an individual. Data acquisition was carried out using the NeuroSky Mindwave Mobile 2 tool to retrieve EEG data.  After the data acquisition is completed, the next process is preprocessing, which is to perform feature extraction using the Fast Furious Transform method to find the average values of the highest and lowest peaks. After the preprocessing is completed go to the classification stage. The classification used is K-Nearest Neighbor with a value of k=9.  For evaluation using confusion matrix to determine the accuracy value of the built KNN model. This study used 100 respondents who were37 people who were addicted to drakor. A total of 24 people out of the 37 or about 64.87% turned out to have a lack of concentration level when taking concentration tests. This is enough to prove that drama impressions can reduce the concentration or focus of a person, especially women. For the classification process to have an accuracy of 80% and for variable correlation testing, it turns out that independent variables do have a simultaneous effect on the dependent variables with a calculated f value of 35.642 and a sig value of 0.000b.
Co-Authors Abbas, Moch Anwar Adys, Himala Praptami Affan, Dhava Chairul Agus Aktawan, Agus Ahmad Barizi Ali, Raden Muhammad Ammattulloh, Fathia Irbati Ammatulloh, Fathia Irbati Ammatulloh, Fathia Irbati Anantatama, Surya Andi Hajar Andi Kamariah Arief, Husniah Arwinsyah Arwinsyah, Arwinsyah Asfah, Indrawaty Asriati Ayu .H, Sendi Sandra Azhari, Cindy Azwar Abbas Bakri Muhammad Bakhiet Budiarti, Gita Indah Danial Hilmi Darmawansyah Alnur, Rony Darmiany Destiyanti, Intan Dharma Ariawan, Ade Dwi Hastuti Dwi Normawati, Dwi Dwiza Riana Dzaki , Arif Rahman Eirene, Jessica Endo, Hiroyuki Endri Junaidi, Endri Enok Sureskiarti Fadlansyah, Holy Faizah Faizah Fariza, Riska Fika Novatiana Furizal, Furizal Gesbi Rizqan Rahman Arief Hadi Saputra Hadi, Muhammad Saepul Hafizh, Achmad Nur Hafizh, Muhammad Naufal Hewiz, Alya Shafira Himala Praptami Adys Husniati Husniati, Husniati Imam Riadi Insan Kamil Sinaga Ismail Ismail Jamilah Jamilah Jaya, Erlangga Jefree Fahana Kamal, Mustapa Kamal, Sofia Kamariah, Andi Kartoirono, Suprihatin Khosyi'ah, Siah Kusaka, Satoshi Kyswantoro, Yunita Firdha Lubis, Dhian Wahyudi Mahmuddin Adriansyah Milkhatun, Milkhatun Muhammad Fahri Jaya Sudding Muhammad Kunta Biddinika Murein Miksa Mardhia Musdalifah Musdalifah Musdalifah Nabila, Ai Negara, Candra Putra nisa, Anisa Shahratul Jannah Nugroho, Prasetiyanto Nur Fatimah Nur Robiah Nofikusumawati Peni Nurfitrah Nuril Anwar, Nuril Octaviantara, Adi Pangistu, Lalu Arfi Maulana Purnaramadhan, Riza Putri, Zelza Alifvia Samudera RAMADAN, RIZKY Robin, Qori Aulia Rosyid A.A, Achmad Rully Charitas Indra Prahmana Safitri, Bunga Sahadi, Syah Reza Pahlevi Sembiring, Surya Anantatama Seny Luhriyani Sunusi Seny Luhriyani Sunusi Setiawan, Dimas Aji Son Ali Akbar Soviyah Sudding, Muhammad Fahri Jaya Suhail, Faiq Surya Anantatama Sembiring Suryanto, Imam Suryanto, Indra Swara, Ajie Kurnia Saputra Syafatullah, Muhammad Rafli Syafrina Lamin, Syafrina Syahriyah, Shilfia Fadhilatul Syuhadak Syuhadak Tanikawa, Kanako Topani, Muhammad Alfikri Maida Tuti Purwaningsih, Tuti Wardoyo, Girindra Sulistiyo Zaman, Azmi Badhi'uz Zaman, Azmi Badhi’uz